class_docstr: Categorical Top-K accuracy. Assumes integer labels, with
  each item to be classified having a single correct class.
  Tie break enables equal distribution of scores among the
  classes with same maximum predicted scores.
code: def reset(self):
      self.correct_count = 0.0
      self.total_count = 0.0
  
file_path: magnitude/pymagnitude/third_party/allennlp/training/metrics/categorical_accuracy.py
imports: from __future__ import division
  from __future__ import absolute_import
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.training.metrics.metric import Metric
label_desc: Use image node_id 4 for calling the CategoricalAccuracy obj's underlying member method code with example usage: obj.reset() without return types